Combining Pattern Classifiers: Methods and Algorithms Ludmila I Kuncheva

ISBN: 9781118914540

Published: August 13th 2014

ebook

384 pages


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Combining Pattern Classifiers: Methods and Algorithms  by  Ludmila I Kuncheva

Combining Pattern Classifiers: Methods and Algorithms by Ludmila I Kuncheva
August 13th 2014 | ebook | PDF, EPUB, FB2, DjVu, audiobook, mp3, ZIP | 384 pages | ISBN: 9781118914540 | 5.67 Mb

A unified, coherent treatment of current classifier ensemble methods, from fundamentals of pattern recognition to ensemble feature selection, now in its second edition The art and science of combining pattern classifiers has flourished into aMoreA unified, coherent treatment of current classifier ensemble methods, from fundamentals of pattern recognition to ensemble feature selection, now in its second edition The art and science of combining pattern classifiers has flourished into a prolific discipline since the first edition of Combining Pattern Classifiers was published in 2004.

Dr. Kuncheva has plucked from the rich landscape of recent classifier ensemble literature the topics, methods, and algorithms that will guide the reader toward a deeper understanding of the fundamentals, design, and applications of classifier ensemble methods.Thoroughly updated, with MATLAB(R) code and practice data sets throughout, Combining Pattern Classifiers includes: Coverage of Bayes decision theory and experimental comparison of classifiers Essential ensemble methods such as Bagging, Random forest, AdaBoost, Random subspace, Rotation forest, Random oracle, and Error Correcting Output Code, among others Chapters on classifier selection, diversity, and ensemble feature selectionWith firm grounding in the fundamentals of pattern recognition, and featuring more than 140 illustrations, Combining Pattern Classifiers, Second Edition is a valuable reference for postgraduate students, researchers, and practitioners in computing and engineering.



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